Welcome to the InfoSci Platform
Sentiment Analysis-Based Categorized Opinions Expressed in Feedback Forums Using Deep Learning Technique and Message Queue Architecture

Sentiment Analysis-Based Categorized Opinions Expressed in Feedback Forums Using Deep Learning Technique and Message Queue Architecture

Upendra Kumar
Copyright: © 2022 |Volume: 14 |Issue: 1 |Pages: 19
ISSN: 2637-7888|EISSN: 2637-7896|EISBN13: 9781683183471|DOI: 10.4018/IJDAI.309743
Cite Article Cite Article

MLA

Kumar, Upendra. "Sentiment Analysis-Based Categorized Opinions Expressed in Feedback Forums Using Deep Learning Technique and Message Queue Architecture." IJDAI vol.14, no.1 2022: pp.1-19. http://doi.org/10.4018/IJDAI.309743

APA

Kumar, U. (2022). Sentiment Analysis-Based Categorized Opinions Expressed in Feedback Forums Using Deep Learning Technique and Message Queue Architecture. International Journal of Distributed Artificial Intelligence (IJDAI), 14(1), 1-19. http://doi.org/10.4018/IJDAI.309743

Chicago

Kumar, Upendra. "Sentiment Analysis-Based Categorized Opinions Expressed in Feedback Forums Using Deep Learning Technique and Message Queue Architecture," International Journal of Distributed Artificial Intelligence (IJDAI) 14, no.1: 1-19. http://doi.org/10.4018/IJDAI.309743

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Sentiment analysis is a sub-field of natural language processing (NLP). In sentiment analysis the sentiment behind the piece of data is tried to know, this data can be a review of a product by a customer or a comment on some social media platform. Analysing large amounts of data is still an easy task for small retail websites and business owners. Deep learning (DL) has made a great revolution in the field of speech and image recognition. Mature deep learning neural network i.e. convolution neural network (CNN) has completely changed the field of NLP. This paper proposed a high accuracy, efficient, scalable, reliable and secure solution to cater all the needs of business owners and institutes for sentiment analysis with DL model, a browser based GUI interface for easy accessibility to all the non-technical folks and a dashboard having graphical representations of their results. The proposed sentiment analysis based model has achieved 93.55% accuracy which has outperformed other models.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.